The present invention relates to a method for enhancing an image using quantized mean-separate histogram equalization (MSHE) and a circuit therefor, and more particularly, to a method and a circuit for implementing the method, in which the input image signals are quantized and split into a predetermined number of sub-images, and then each sub-image is independently histogram-equalized.
The histogram of gray levels completely describes the appearance of an image. Properly adjusting the gray levels for a given image enhances the appearance or the contrast of the image.
Among the various types of methods used for enhancing the contrast of an image, histogram-equalization, which enhances the contrast of a given image according to the sample distribution of the image is most widely known and disclosed in the following documents: 1! J. S. Lim, "Two-Dimensional Signal and Image Processing", Prentice Hall, Englewood Cliffs, N.J., 1990; and 2! R. C. Gonzales and P. Wints, "Digital Image Processing", Addition-Wesley, Reading, Mass., 1977.
In addition, useful applications of the histogram-equalization method, including medical image processing and a radar image processing, are disclosed in the following documents: 3! J. Zimmerman, S. Pizer, E. Staab, E. Perry, W. McCartney and B. Breton, "Evaluation of the Effectiveness of Adaptive Histogram Equalization for Contrast Enhancement," IEEE Tr. on Medical Imaging, pp. 304-312, Dec. 1988; and 4! Y. Li, W. Wang and D. Y. Yu, "Application of Adaptive Histogram Equalization to X-ray Chest Image," Proc. of the SPIE, pp. 513-514, vol. 2321, 1994.
Generally, since histogram equalization extends through the dynamic range, the distribution density of the resultant image is made uniform. As a result, the contrast of the image is enhanced.
This widely known characteristic of histogram equalization is disadvantageous in some cases. That is, because the output density of the histogram equalization is uniform, the mean brightness of an output image is near the middle of the gray level range.
Actually for the histogram equalization of an analog image, the mean brightness of the output image due to the histogram equalization is the middle gray level regardless of the mean brightness of the input image. This characteristic is undesirable for some applications. For instance, the fact that an image taken in the night looks like an image taken in the daytime after histogram equalization is a problem.
In addition, because the conventional histogram equalizer requires the storage of each gray level number, the cost for hardware is high. For example, if 256 gray levels (L) are used, 256 memory devices are required for storing the occurrence numbers of all levels, and 256 accumulators are required for accumulating every occurrence number of each level.